------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\sgolder\Dropbox\Portfolio Allocation\replication\africancabinets_multi_region.log
  log type:  text
 opened on:  30 Mar 2017, 13:36:51

. set more off

. #delimit ;
delimiter now ;
. *     ***************************************************************** *;
. *     ***************************************************************** *;
. *       File-Name:      africancabinets16_multi_region.do               *;
. *       Date:           March 22, 2017                                  *;
. *       Author:         Molly Ariotti and Sona Golder                   *;
. *       Purpose:        Replicate results for CPS African portfolio     *;
. *                       allocation paper, using Africa data 1990-2014.  *;
. *           Input File:     Africa.dta, Europe.dta, America.dta             *;
. *       Output File:    africancabinets16_multi_region.log              *;
. *       Data Output:    none                                            *;
.              *       Previous file:  none                                            *;
. *       Machine:        laptop                                                          *;
. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *       Open and summarize dataset.                                     *;
. *     ****************************************************************  *;
. use "\Users\sgolder\Dropbox\Portfolio Allocation\replication\Africa.dta";

.  sum;

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
 countryname |          0
 countrycode |         84    5.559524    2.552349          1          9
 cabinetcode |         84    13.89286    8.034591          1         28
     cowcode |         84    517.8452    69.14373        403        590
        year |         84    2002.357    6.825965       1990       2014
-------------+---------------------------------------------------------
presidential |         84    .3690476    .4854451          0          1
   formateur |         84    .3095238    .4650739          0          1
  portfolios |         84     7.02381    6.860005          1         26
governmen~os |         84    21.08333    6.637259          9         35
 party_seats |         84    39.91667    56.69368          1        279
-------------+---------------------------------------------------------
governmen~ts |         84    115.0952    86.61028         39        377
      region |         84           1           0          1          1
portfolios~e |         84    .3333333     .282168   .0344828   .9545454
   seatshare |         84    .3333333    .2628826   .0034843    .990099
       party |         84    25.91667    13.80083          1         48
-------------+---------------------------------------------------------
        code |         84    105573.4    2560.162     101001     109028

. desc;

Contains data from \Users\sgolder\Dropbox\Portfolio Allocation\replication\Africa.dta
  obs:            84                          
 vars:            16                          30 Mar 2017 12:13
 size:         4,368                          
------------------------------------------------------------------------------------------------------------------
              storage   display    value
variable name   type    format     label      variable label
------------------------------------------------------------------------------------------------------------------
countryname     str21   %21s                  country name
countrycode     byte    %8.0g                 country code
cabinetcode     byte    %8.0g                 cabinet code
cowcode         int     %8.0g                 cow code
year            int     %8.0g                 year in which government begins
presidential    byte    %8.0g                 1 = presidential, 0 = parliamentary
formateur       byte    %8.0g                 1 = formateur, 0 = otherwise
portfolios      byte    %8.0g                 number of portfolios per party
government_po~s byte    %8.0g                 number of portfolios in the government
party_seats     int     %8.0g                 number of legislative seats per party
government_se~s int     %8.0g                 number of seats controlled by government
region          byte    %8.0g                 1=Africa, 2=Western Europe, 3=Latin America
portfolioshare  float   %9.0g                 party share of govt portfolios
seatshare       float   %9.0g                 party share of leg seats controlled by govt
party           long    %9.0g      party      party number or acronym
code            float   %9.0g                 region, country code, cabinet code
------------------------------------------------------------------------------------------------------------------
Sorted by: 

. *     ****************************************************************  *;
. *       Drop African cabinets where there is no formateur coded.        *;
. *       (One in Guinea-Bissau, one in Sao Tome & Principe               *;
. *     ****************************************************************  *;
. drop if cabinetcode == 5;
(5 observations deleted)

. drop if cabinetcode == 23;
(3 observations deleted)

. *     ****************************************************************  *;
. *       Add Europe data from Warwick and Druckman (2006)                *;
. *     ****************************************************************  *;
. append using "\Users\sgolder\Dropbox\Portfolio Allocation\replication\Europe.dta";
(note: variable year was int, now float to accommodate using data's values)
(note: variable party was long, now double to accommodate using data's values)
(note: variable party_seats was int, now float to accommodate using data's values)
(note: variable formateur was byte, now float to accommodate using data's values)
(note: variable government_portfolios was byte, now float to accommodate using data's values)
(note: variable countrycode was byte, now float to accommodate using data's values)
(note: variable portfolios was byte, now float to accommodate using data's values)
(note: variable cabinetcode was byte, now float to accommodate using data's values)
(note: variable region was byte, now float to accommodate using data's values)
(note: variable cowcode was int, now float to accommodate using data's values)
(note: variable government_seats was int, now float to accommodate using data's values)
(note: variable presidential was byte, now float to accommodate using data's values)

.  *     ****************************************************************  *;
. *       Drop European cabinets where there is no formateur coded.       *;
. *      (These are caseno 531, 532, 533, 534, 542,543, 617, 858, 859)    *;
. *     ****************************************************************  *;
. drop if code == 205097;
(3 observations deleted)

. drop if code == 205098;
(2 observations deleted)

. drop if code == 205099;
(2 observations deleted)

. drop if code == 205100;
(2 observations deleted)

. drop if code == 205108;
(4 observations deleted)

. drop if code == 205109;
(4 observations deleted)

. drop if code == 207130;
(3 observations deleted)

. drop if code == 209184;
(6 observations deleted)

. drop if code == 209185;
(4 observations deleted)

. *     ****************************************************************  *;
. *       Add Latin American data from Almeida (2003)                     *;
. *     ****************************************************************  *;
. append using "\Users\sgolder\Dropbox\Portfolio Allocation\replication\America.dta";
(label party already defined)

.  *     ****************************************************************  *;
. *       Create regional dummy variables                                 *;
. *     ****************************************************************  *;
. gen africa = . ;
(1,068 missing values generated)

. replace africa = 1 if region==1;
(76 real changes made)

. replace africa = 0 if region==2;
(777 real changes made)

. replace africa = 0 if region==3;
(215 real changes made)

. gen europe = . ;
(1,068 missing values generated)

. replace europe = 0 if region==1;
(76 real changes made)

. replace europe = 1 if region==2;
(777 real changes made)

. replace europe = 0 if region==3;
(215 real changes made)

. gen america = . ;
(1,068 missing values generated)

. replace america = 0 if region==1;
(76 real changes made)

. replace america = 0 if region==2;
(777 real changes made)

. replace america = 1 if region==3;
(215 real changes made)

. *     ****************************************************************  *;
. *       Create interaction terms for analysis in Table 1                *;
. *     ****************************************************************  *;
. gen seatshare_africa=africa*seatshare;

. gen formateur_africa=africa*formateur;

. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *       Produce results in Table 2 (without formateur).                 *;
. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *       Model 1 combined (Africa + Europe), 285 cabinets                *;
. *     ****************************************************************  *;
. regress portfolioshare seatshare africa seatshare_africa if region != 3, robust;

Linear regression                               Number of obs     =        853
                                                F(3, 849)         =    2639.57
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9023
                                                Root MSE          =     .06695

----------------------------------------------------------------------------------
                 |               Robust
  portfolioshare |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
       seatshare |   .7912453   .0098434    80.38   0.000     .7719251    .8105655
          africa |  -.0855797   .0103812    -8.24   0.000    -.1059555   -.0652039
seatshare_africa |   .2555087   .0297672     8.58   0.000     .1970828    .3139346
           _cons |   .0695849   .0035713    19.48   0.000     .0625752    .0765946
----------------------------------------------------------------------------------

. *     ****************************************************************  *;
. *       Model 2 Europe, 259 cabinets                                    *;
. *     ****************************************************************  *;
. regress portfolioshare seatshare if europe==1, robust;

Linear regression                               Number of obs     =        777
                                                F(1, 775)         =    6475.24
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8946
                                                Root MSE          =     .06662

------------------------------------------------------------------------------
             |               Robust
portfolios~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   seatshare |   .7912453   .0098329    80.47   0.000     .7719429    .8105476
       _cons |   .0695849   .0035675    19.50   0.000     .0625817    .0765881
------------------------------------------------------------------------------

. *     ****************************************************************  *;
. *       Is coefficient on seatshare 1? [No.]                              *;
. *     ****************************************************************  *;
. test seatshare=1;

 ( 1)  seatshare = 1

       F(  1,   775) =  450.72
            Prob > F =    0.0000

. *     ****************************************************************  *;
. *       Model 3 Africa, 26 cabinets                                     *;
. *     ****************************************************************  *;
. regress portfolioshare seatshare if africa==1, robust;

Linear regression                               Number of obs     =         76
                                                F(1, 74)          =    1358.20
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9421
                                                Root MSE          =     .07032

------------------------------------------------------------------------------
             |               Robust
portfolios~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   seatshare |   1.046754   .0284029    36.85   0.000       .99016    1.103348
       _cons |  -.0159948   .0098552    -1.62   0.109    -.0356317    .0036421
------------------------------------------------------------------------------

. *     ****************************************************************  *;
. *       Is coefficient on seatshare 1? [Cannot reject]                  *;
. *     ****************************************************************  *;
. test seatshare=1;

 ( 1)  seatshare = 1

       F(  1,    74) =    2.71
            Prob > F =    0.1040

. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *       Produce results in Table 2 (with formateur).                    *;
. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *       Model 4 combined (Africa + Europe)                              *;
. *     ****************************************************************  *;
.  regress portfolioshare seatshare formateur africa seatshare_africa formateur_africa  if region != 3, robust;

Linear regression                               Number of obs     =        853
                                                F(5, 847)         =    1713.93
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9069
                                                Root MSE          =     .06546

----------------------------------------------------------------------------------
                 |               Robust
  portfolioshare |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
       seatshare |   .8346488   .0137715    60.61   0.000     .8076186    .8616789
       formateur |  -.0310149   .0073525    -4.22   0.000    -.0454462   -.0165837
          africa |  -.0614534   .0086882    -7.07   0.000    -.0785063   -.0444005
seatshare_africa |   .0230141   .0403582     0.57   0.569    -.0561997    .1022279
formateur_africa |    .161654   .0268466     6.02   0.000     .1089602    .2143477
           _cons |   .0654554   .0035636    18.37   0.000     .0584608      .07245
----------------------------------------------------------------------------------

. lincom formateur + formateur_africa;

 ( 1)  formateur + formateur_africa = 0

------------------------------------------------------------------------------
portfolios~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |    .130639   .0258202     5.06   0.000     .0799599    .1813181
------------------------------------------------------------------------------

. *     ****************************************************************  *;
. *       Model 5 Europe                                                  *;
. *     ****************************************************************  *;
. regress portfolioshare seatshare formateur if europe==1, robust;

Linear regression                               Number of obs     =        777
                                                F(2, 774)         =    3252.65
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8970
                                                Root MSE          =      .0659

------------------------------------------------------------------------------
             |               Robust
portfolios~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   seatshare |   .8346488   .0137495    60.70   0.000      .807658    .8616395
   formateur |  -.0310149   .0073408    -4.23   0.000    -.0454251   -.0166047
       _cons |   .0654554   .0035579    18.40   0.000      .058471    .0724398
------------------------------------------------------------------------------

. *     ****************************************************************  *;
. *       Model 6 Africa                                                  *;
. *     ****************************************************************  *;
. regress portfolioshare seatshare formateur if africa==1, robust;

Linear regression                               Number of obs     =         76
                                                F(2, 73)          =     941.62
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9575
                                                Root MSE          =     .06062

------------------------------------------------------------------------------
             |               Robust
portfolios~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   seatshare |   .8576629   .0385712    22.24   0.000     .7807907    .9345351
   formateur |    .130639   .0262526     4.98   0.000     .0783177    .1829604
       _cons |    .004002   .0080564     0.50   0.621    -.0120544    .0200584
------------------------------------------------------------------------------

. *     ****************************************************************  *;
.  *       Replication of Table 2 in main text complete                    *;
. *     ****************************************************************  *;
.  *     ****************************************************************  *;
. *                   Supplementary Analyses                              *;
. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *       Run models for Table in Appendix C (similar to Table 1, but     *;
. *       including Latin American data.                                  *;
. *       Note that Latin American data comprises 215 cabinet parties     *;
. *       in 74 cabinets in 10 countries                                  *;
. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *       Model 1 Europe                                                  *;
. *     ****************************************************************  *;
. regress portfolioshare seatshare formateur if region==2, robust;

Linear regression                               Number of obs     =        777
                                                F(2, 774)         =    3252.65
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8970
                                                Root MSE          =      .0659

------------------------------------------------------------------------------
             |               Robust
portfolios~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   seatshare |   .8346488   .0137495    60.70   0.000      .807658    .8616395
   formateur |  -.0310149   .0073408    -4.23   0.000    -.0454251   -.0166047
       _cons |   .0654554   .0035579    18.40   0.000      .058471    .0724398
------------------------------------------------------------------------------

. *     ****************************************************************  *;
. *       Model 2 Latin America                                           *;
. *     ****************************************************************  *;
. regress portfolioshare seatshare formateur if region==3, robust;

Linear regression                               Number of obs     =        215
                                                F(2, 212)         =     274.42
                                                Prob > F          =     0.0000
                                                R-squared         =     0.7541
                                                Root MSE          =     .11816

------------------------------------------------------------------------------
             |               Robust
portfolios~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   seatshare |   .5409083    .045613    11.86   0.000     .4509952    .6308215
   formateur |   .1829649    .025474     7.18   0.000     .1327501    .2331798
       _cons |    .094944   .0113478     8.37   0.000     .0725749     .117313
------------------------------------------------------------------------------

. *     ****************************************************************  *;
. *       Model 3 Africa Pooled                                           *;
. *     ****************************************************************  *;
. regress portfolioshare seatshare formateur if region==1, robust;

Linear regression                               Number of obs     =         76
                                                F(2, 73)          =     941.62
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9575
                                                Root MSE          =     .06062

------------------------------------------------------------------------------
             |               Robust
portfolios~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   seatshare |   .8576629   .0385712    22.24   0.000     .7807907    .9345351
   formateur |    .130639   .0262526     4.98   0.000     .0783177    .1829604
       _cons |    .004002   .0080564     0.50   0.621    -.0120544    .0200584
------------------------------------------------------------------------------

. *     ****************************************************************  *;
. *       Model 4 Africa Parliamentary                                    *;
. *     ****************************************************************  *;
. regress portfolioshare seatshare formateur if region==1 & presidential==0, robust;

Linear regression                               Number of obs     =         45
                                                F(2, 42)          =     758.45
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9711
                                                Root MSE          =     .04615

------------------------------------------------------------------------------
             |               Robust
portfolios~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   seatshare |   .9038053   .0388323    23.27   0.000     .8254386     .982172
   formateur |   .0572177   .0237512     2.41   0.020     .0092859    .1051495
       _cons |   .0129924   .0090057     1.44   0.157    -.0051819    .0311666
------------------------------------------------------------------------------

. *     ****************************************************************  *;
. *       Model 5 Africa Presidential                                     *;
. *     ****************************************************************  *;
. regress portfolioshare seatshare formateur if region==1 & presidential==1, robust;

Linear regression                               Number of obs     =         31
                                                F(2, 28)          =     472.88
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9676
                                                Root MSE          =     .06103

------------------------------------------------------------------------------
             |               Robust
portfolios~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   seatshare |   .7736803    .075247    10.28   0.000     .6195438    .9278167
   formateur |   .2448744   .0499857     4.90   0.000     .1424833    .3472655
       _cons |  -.0065839    .014541    -0.45   0.654    -.0363697    .0232019
------------------------------------------------------------------------------

. *     ****************************************************************  *;
.  *       Table 2 Robustness check with clustering - results robust       *;
. *     ****************************************************************  *;
.  regress portfolioshare seatshare africa seatshare_africa if region != 3, cluster(cabinetcode);

Linear regression                               Number of obs     =        853
                                                F(3, 258)         =    1761.90
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9023
                                                Root MSE          =     .06695

                              (Std. Err. adjusted for 259 clusters in cabinetcode)
----------------------------------------------------------------------------------
                 |               Robust
  portfolioshare |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
       seatshare |   .7912453   .0115277    68.64   0.000     .7685449    .8139457
          africa |  -.0855797   .0123871    -6.91   0.000    -.1099724    -.061187
seatshare_africa |   .2555087   .0356744     7.16   0.000     .1852587    .3257587
           _cons |   .0695849   .0042751    16.28   0.000     .0611663    .0780035
----------------------------------------------------------------------------------

. regress portfolioshare seatshare if europe==1, cluster(cabinetcode);

Linear regression                               Number of obs     =        777
                                                F(1, 258)         =    4721.79
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8946
                                                Root MSE          =     .06662

                          (Std. Err. adjusted for 259 clusters in cabinetcode)
------------------------------------------------------------------------------
             |               Robust
portfolios~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   seatshare |   .7912453   .0115148    68.72   0.000     .7685703    .8139203
       _cons |   .0695849   .0042703    16.29   0.000     .0611757    .0779941
------------------------------------------------------------------------------

. regress portfolioshare seatshare if africa==1, cluster(cabinetcode);

Linear regression                               Number of obs     =         76
                                                F(1, 25)          =     863.36
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9421
                                                Root MSE          =     .07032

                           (Std. Err. adjusted for 26 clusters in cabinetcode)
------------------------------------------------------------------------------
             |               Robust
portfolios~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   seatshare |   1.046754   .0356246    29.38   0.000     .9733838    1.120124
       _cons |  -.0159948   .0122461    -1.31   0.203     -.041216    .0092265
------------------------------------------------------------------------------

. regress portfolioshare seatshare formateur africa seatshare_africa formateur_africa if region != 3, cluster(cabi
> netcode);

Linear regression                               Number of obs     =        853
                                                F(5, 258)         =    1155.67
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9069
                                                Root MSE          =     .06546

                              (Std. Err. adjusted for 259 clusters in cabinetcode)
----------------------------------------------------------------------------------
                 |               Robust
  portfolioshare |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
       seatshare |   .8346488   .0155584    53.65   0.000     .8040112    .8652863
       formateur |  -.0310149   .0089246    -3.48   0.001    -.0485892   -.0134406
          africa |  -.0614534   .0094598    -6.50   0.000    -.0800816   -.0428252
seatshare_africa |   .0230141   .0469763     0.49   0.625    -.0694918      .11552
formateur_africa |    .161654   .0356201     4.54   0.000     .0915108    .2317971
           _cons |   .0654554   .0042235    15.50   0.000     .0571385    .0737723
----------------------------------------------------------------------------------

. regress portfolioshare seatshare formateur if europe==1, cluster(cabinetcode);

Linear regression                               Number of obs     =        777
                                                F(2, 258)         =    2428.19
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8970
                                                Root MSE          =      .0659

                          (Std. Err. adjusted for 259 clusters in cabinetcode)
------------------------------------------------------------------------------
             |               Robust
portfolios~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   seatshare |   .8346488   .0155327    53.73   0.000     .8040617    .8652358
   formateur |  -.0310149   .0089098    -3.48   0.001    -.0485602   -.0134696
       _cons |   .0654554   .0042165    15.52   0.000     .0571522    .0737586
------------------------------------------------------------------------------

. regress portfolioshare seatshare formateur if africa==1, cluster(cabinetcode);

Linear regression                               Number of obs     =         76
                                                F(2, 25)          =     691.90
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9575
                                                Root MSE          =     .06062

                           (Std. Err. adjusted for 26 clusters in cabinetcode)
------------------------------------------------------------------------------
             |               Robust
portfolios~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   seatshare |   .8576629   .0461002    18.60   0.000     .7627178     .952608
   formateur |    .130639   .0357541     3.65   0.001     .0570021     .204276
       _cons |    .004002   .0091851     0.44   0.667    -.0149152    .0229191
------------------------------------------------------------------------------

. *     ****************************************************************  *;
.  *       Repeat with bootstrap clustering - results robust.              *;
. *     ****************************************************************  *;
.  regress portfolioshare seatshare africa seatshare_africa if region != 3, vce(boot, cluster(cabinetcode) reps(40
> 0) seed(10101));
(running regress on estimation sample)

Bootstrap replications (400)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..................................................    50
..................................................   100
..................................................   150
..................................................   200
..................................................   250
..................................................   300
..................................................   350
..................................................   400

Linear regression                               Number of obs     =        853
                                                Replications      =        400
                                                Wald chi2(3)      =    5547.02
                                                Prob > chi2       =     0.0000
                                                R-squared         =     0.9023
                                                Adj R-squared     =     0.9020
                                                Root MSE          =     0.0670

                               (Replications based on 259 clusters in cabinetcode)
----------------------------------------------------------------------------------
                 |   Observed   Bootstrap                         Normal-based
  portfolioshare |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
       seatshare |   .7912453   .0112822    70.13   0.000     .7691326     .813358
          africa |  -.0855797    .013533    -6.32   0.000    -.1121038   -.0590555
seatshare_africa |   .2555087   .0385569     6.63   0.000     .1799386    .3310788
           _cons |   .0695849   .0042135    16.51   0.000     .0613266    .0778432
----------------------------------------------------------------------------------

. regress portfolioshare seatshare if europe==1, vce(boot, cluster(cabinetcode) reps(400) seed(10101));
(running regress on estimation sample)

Bootstrap replications (400)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..................................................    50
..................................................   100
..................................................   150
..................................................   200
..................................................   250
..................................................   300
..................................................   350
..................................................   400

Linear regression                               Number of obs     =        777
                                                Replications      =        400
                                                Wald chi2(1)      =    4918.52
                                                Prob > chi2       =     0.0000
                                                R-squared         =     0.8946
                                                Adj R-squared     =     0.8945
                                                Root MSE          =     0.0666

                           (Replications based on 259 clusters in cabinetcode)
------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
portfolios~e |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   seatshare |   .7912453   .0112822    70.13   0.000     .7691326     .813358
       _cons |   .0695849   .0042135    16.51   0.000     .0613266    .0778432
------------------------------------------------------------------------------

. regress portfolioshare seatshare if africa==1, vce(boot, cluster(cabinetcode) reps(400) seed(10101));
(running regress on estimation sample)

Bootstrap replications (400)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..................................................    50
..................................................   100
..................................................   150
..................................................   200
..................................................   250
..................................................   300
..................................................   350
..................................................   400

Linear regression                               Number of obs     =         76
                                                Replications      =        400
                                                Wald chi2(1)      =     862.51
                                                Prob > chi2       =     0.0000
                                                R-squared         =     0.9421
                                                Adj R-squared     =     0.9413
                                                Root MSE          =     0.0703

                            (Replications based on 26 clusters in cabinetcode)
------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
portfolios~e |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   seatshare |   1.046754    .035642    29.37   0.000      .976897    1.116611
       _cons |  -.0159948   .0123181    -1.30   0.194    -.0401378    .0081482
------------------------------------------------------------------------------

. regress portfolioshare seatshare formateur africa seatshare_africa formateur_africa if region != 3, vce(boot, cl
> uster(cabinetcode) reps(400) seed(10101));
(running regress on estimation sample)

Bootstrap replications (400)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..................................................    50
..................................................   100
..................................................   150
..................................................   200
..................................................   250
..................................................   300
..................................................   350
..................................................   400

Linear regression                               Number of obs     =        853
                                                Replications      =        400
                                                Wald chi2(5)      =    6197.97
                                                Prob > chi2       =     0.0000
                                                R-squared         =     0.9069
                                                Adj R-squared     =     0.9063
                                                Root MSE          =     0.0655

                               (Replications based on 259 clusters in cabinetcode)
----------------------------------------------------------------------------------
                 |   Observed   Bootstrap                         Normal-based
  portfolioshare |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
       seatshare |   .8346488   .0151338    55.15   0.000      .804987    .8643105
       formateur |  -.0310149   .0091107    -3.40   0.001    -.0488715   -.0131583
          africa |  -.0614534    .010471    -5.87   0.000    -.0819762   -.0409307
seatshare_africa |   .0230141   .0485542     0.47   0.636    -.0721503    .1181786
formateur_africa |    .161654   .0370291     4.37   0.000     .0890783    .2342296
           _cons |   .0654554   .0040667    16.10   0.000     .0574847     .073426
----------------------------------------------------------------------------------

. regress portfolioshare seatshare formateur if europe==1, vce(boot, cluster(cabinetcode) reps(400) seed(10101));
(running regress on estimation sample)

Bootstrap replications (400)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..................................................    50
..................................................   100
..................................................   150
..................................................   200
..................................................   250
..................................................   300
..................................................   350
..................................................   400

Linear regression                               Number of obs     =        777
                                                Replications      =        400
                                                Wald chi2(2)      =    5210.98
                                                Prob > chi2       =     0.0000
                                                R-squared         =     0.8970
                                                Adj R-squared     =     0.8968
                                                Root MSE          =     0.0659

                           (Replications based on 259 clusters in cabinetcode)
------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
portfolios~e |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   seatshare |   .8346488   .0151338    55.15   0.000      .804987    .8643105
   formateur |  -.0310149   .0091107    -3.40   0.001    -.0488715   -.0131583
       _cons |   .0654554   .0040667    16.10   0.000     .0574847     .073426
------------------------------------------------------------------------------

. regress portfolioshare seatshare formateur if africa==1, vce(boot, cluster(cabinetcode) reps(400) seed(10101));
(running regress on estimation sample)

Bootstrap replications (400)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..................................................    50
..................................................   100
..................................................   150
..................................................   200
..................................................   250
..................................................   300
..................................................   350
..................................................   400

Linear regression                               Number of obs     =         76
                                                Replications      =        400
                                                Wald chi2(2)      =    1322.23
                                                Prob > chi2       =     0.0000
                                                R-squared         =     0.9575
                                                Adj R-squared     =     0.9564
                                                Root MSE          =     0.0606

                            (Replications based on 26 clusters in cabinetcode)
------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
portfolios~e |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   seatshare |   .8576629   .0474498    18.08   0.000     .7646629    .9506629
   formateur |    .130639   .0352919     3.70   0.000     .0614682    .1998099
       _cons |    .004002   .0096558     0.41   0.679     -.014923     .022927
------------------------------------------------------------------------------

. *     ****************************************************************  *;
. *       Jacknife procedures (drop one government)                       *;
. *     ****************************************************************  *;
. regress portfolioshare seatshare africa seatshare_africa if region != 3, vce(jackknife, cluster(cabinetcode));
(running regress on estimation sample)

Jackknife replications (259)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..................................................    50
..................................................   100
..................................................   150
..................................................   200
..................................................   250
.........

Linear regression                               Number of obs     =        853
                                                Replications      =        259
                                                F(   3,    258)   =    1741.97
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9023
                                                Adj R-squared     =     0.9020
                                                Root MSE          =     0.0670

                               (Replications based on 259 clusters in cabinetcode)
----------------------------------------------------------------------------------
                 |              Jackknife
  portfolioshare |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
       seatshare |   .7912453   .0115313    68.62   0.000     .7685377    .8139528
          africa |  -.0855797   .0129392    -6.61   0.000    -.1110595   -.0600999
seatshare_africa |   .2555087   .0374588     6.82   0.000     .1817448    .3292725
           _cons |   .0695849   .0042764    16.27   0.000     .0611638     .078006
----------------------------------------------------------------------------------

. regress portfolioshare seatshare if europe==1, vce(jackknife, cluster(cabinetcode));
(running regress on estimation sample)

Jackknife replications (259)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..................................................    50
..................................................   100
..................................................   150
..................................................   200
..................................................   250
.........

Linear regression                               Number of obs     =        777
                                                Replications      =        259
                                                F(   1,    258)   =    4708.28
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8946
                                                Adj R-squared     =     0.8945
                                                Root MSE          =     0.0666

                           (Replications based on 259 clusters in cabinetcode)
------------------------------------------------------------------------------
             |              Jackknife
portfolios~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   seatshare |   .7912453   .0115313    68.62   0.000     .7685377    .8139528
       _cons |   .0695849   .0042764    16.27   0.000     .0611638     .078006
------------------------------------------------------------------------------

. regress portfolioshare seatshare if africa==1, vce(jackknife, cluster(cabinetcode));
(running regress on estimation sample)

Jackknife replications (26)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..........................

Linear regression                               Number of obs     =         76
                                                Replications      =         26
                                                F(   1,     25)   =     844.17
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9421
                                                Adj R-squared     =     0.9413
                                                Root MSE          =     0.0703

                            (Replications based on 26 clusters in cabinetcode)
------------------------------------------------------------------------------
             |              Jackknife
portfolios~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   seatshare |   1.046754   .0360272    29.05   0.000     .9725546    1.120953
       _cons |  -.0159948   .0123319    -1.30   0.206    -.0413928    .0094033
------------------------------------------------------------------------------

. regress portfolioshare seatshare formateur africa seatshare_africa formateur_africa if region != 3, vce(jackknif
> e, cluster(cabinetcode));
(running regress on estimation sample)

Jackknife replications (259)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..................................................    50
..................................................   100
..................................................   150
..................................................   200
..................................................   250
.........

Linear regression                               Number of obs     =        853
                                                Replications      =        259
                                                F(   5,    258)   =    1127.09
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9069
                                                Adj R-squared     =     0.9063
                                                Root MSE          =     0.0655

                               (Replications based on 259 clusters in cabinetcode)
----------------------------------------------------------------------------------
                 |              Jackknife
  portfolioshare |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
       seatshare |   .8346488   .0156295    53.40   0.000      .803871    .8654265
       formateur |  -.0310149   .0089439    -3.47   0.001    -.0486273   -.0134026
          africa |  -.0614534   .0099974    -6.15   0.000    -.0811403   -.0417665
seatshare_africa |   .0230141   .0509773     0.45   0.652    -.0773705    .1233987
formateur_africa |    .161654   .0380317     4.25   0.000      .086762    .2365459
           _cons |   .0654554   .0042292    15.48   0.000     .0571272    .0737836
----------------------------------------------------------------------------------

. regress portfolioshare seatshare formateur if europe==1, vce(jackknife, cluster(cabinetcode));
(running regress on estimation sample)

Jackknife replications (259)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..................................................    50
..................................................   100
..................................................   150
..................................................   200
..................................................   250
.........

Linear regression                               Number of obs     =        777
                                                Replications      =        259
                                                F(   2,    258)   =    2412.90
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8970
                                                Adj R-squared     =     0.8968
                                                Root MSE          =     0.0659

                           (Replications based on 259 clusters in cabinetcode)
------------------------------------------------------------------------------
             |              Jackknife
portfolios~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   seatshare |   .8346488   .0156295    53.40   0.000      .803871    .8654265
   formateur |  -.0310149   .0089439    -3.47   0.001    -.0486273   -.0134026
       _cons |   .0654554   .0042292    15.48   0.000     .0571272    .0737836
------------------------------------------------------------------------------

. regress portfolioshare seatshare formateur if africa==1, vce(jackknife, cluster(cabinetcode));
(running regress on estimation sample)

Jackknife replications (26)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..........................

Linear regression                               Number of obs     =         76
                                                Replications      =         26
                                                F(   2,     25)   =     672.95
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9575
                                                Adj R-squared     =     0.9564
                                                Root MSE          =     0.0606

                            (Replications based on 26 clusters in cabinetcode)
------------------------------------------------------------------------------
             |              Jackknife
portfolios~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   seatshare |   .8576629   .0481278    17.82   0.000     .7585418    .9567839
   formateur |    .130639   .0365818     3.57   0.001     .0552974    .2059807
       _cons |    .004002   .0093375     0.43   0.672     -.015229     .023233
------------------------------------------------------------------------------

. *     ****************************************************************  *;
. *       Jacknife procedures (drop one country)                          *;
. *     ****************************************************************  *;
. regress portfolioshare seatshare africa seatshare_africa if region != 3, vce(jackknife, cluster(countrycode));
(running regress on estimation sample)

Jackknife replications (14)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..............

Linear regression                               Number of obs     =        853
                                                Replications      =         14
                                                F(   3,     13)   =     332.64
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9023
                                                Adj R-squared     =     0.9020
                                                Root MSE          =     0.0670

                                (Replications based on 14 clusters in countrycode)
----------------------------------------------------------------------------------
                 |              Jackknife
  portfolioshare |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
       seatshare |   .7912453   .0287057    27.56   0.000     .7292304    .8532602
          africa |  -.0855797   .0148255    -5.77   0.000    -.1176082   -.0535512
seatshare_africa |   .2555087   .0388137     6.58   0.000     .1716567    .3393606
           _cons |   .0695849   .0105897     6.57   0.000     .0467074    .0924625
----------------------------------------------------------------------------------

. regress portfolioshare seatshare if europe==1, vce(jackknife, cluster(countrycode));
(running regress on estimation sample)

Jackknife replications (14)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..............

Linear regression                               Number of obs     =        777
                                                Replications      =         14
                                                F(   1,     13)   =     759.78
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8946
                                                Adj R-squared     =     0.8945
                                                Root MSE          =     0.0666

                            (Replications based on 14 clusters in countrycode)
------------------------------------------------------------------------------
             |              Jackknife
portfolios~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   seatshare |   .7912453   .0287057    27.56   0.000     .7292304    .8532602
       _cons |   .0695849   .0105897     6.57   0.000     .0467074    .0924625
------------------------------------------------------------------------------

. regress portfolioshare seatshare if africa==1, vce(jackknife, cluster(countrycode));
(running regress on estimation sample)

Jackknife replications (9)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
.........

Linear regression                               Number of obs     =         76
                                                Replications      =          9
                                                F(   1,      8)   =     651.87
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9421
                                                Adj R-squared     =     0.9413
                                                Root MSE          =     0.0703

                             (Replications based on 9 clusters in countrycode)
------------------------------------------------------------------------------
             |              Jackknife
portfolios~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   seatshare |   1.046754   .0409981    25.53   0.000     .9522122    1.141296
       _cons |  -.0159948   .0138397    -1.16   0.281    -.0479092    .0159196
------------------------------------------------------------------------------

. regress portfolioshare seatshare formateur africa seatshare_africa formateur_africa if region != 3, vce(jackknif
> e, cluster(countrycode));
(running regress on estimation sample)

Jackknife replications (14)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..............

Linear regression                               Number of obs     =        853
                                                Replications      =         14
                                                F(   5,     13)   =     583.30
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9069
                                                Adj R-squared     =     0.9063
                                                Root MSE          =     0.0655

                                (Replications based on 14 clusters in countrycode)
----------------------------------------------------------------------------------
                 |              Jackknife
  portfolioshare |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
       seatshare |   .8346488   .0432453    19.30   0.000      .741223    .9280745
       formateur |  -.0310149    .015298    -2.03   0.064    -.0640643    .0020345
          africa |  -.0614534   .0141148    -4.35   0.001    -.0919466   -.0309602
seatshare_africa |   .0230141   .0645233     0.36   0.727    -.1163801    .1624083
formateur_africa |    .161654   .0444878     3.63   0.003     .0655439     .257764
           _cons |   .0654554   .0116652     5.61   0.000     .0402543    .0906565
----------------------------------------------------------------------------------

. regress portfolioshare seatshare formateur if europe==1, vce(jackknife, cluster(countrycode));
(running regress on estimation sample)

Jackknife replications (14)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..............

Linear regression                               Number of obs     =        777
                                                Replications      =         14
                                                F(   2,     13)   =     301.50
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8970
                                                Adj R-squared     =     0.8968
                                                Root MSE          =     0.0659

                            (Replications based on 14 clusters in countrycode)
------------------------------------------------------------------------------
             |              Jackknife
portfolios~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   seatshare |   .8346488   .0432453    19.30   0.000      .741223    .9280745
   formateur |  -.0310149    .015298    -2.03   0.064    -.0640643    .0020345
       _cons |   .0654554   .0116652     5.61   0.000     .0402543    .0906565
------------------------------------------------------------------------------

. regress portfolioshare seatshare formateur if africa==1, vce(jackknife, cluster(countrycode));
(running regress on estimation sample)

Jackknife replications (9)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
.........

Linear regression                               Number of obs     =         76
                                                Replications      =          9
                                                F(   2,      8)   =     711.47
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9575
                                                Adj R-squared     =     0.9564
                                                Root MSE          =     0.0606

                             (Replications based on 9 clusters in countrycode)
------------------------------------------------------------------------------
             |              Jackknife
portfolios~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   seatshare |   .8576629   .0449914    19.06   0.000     .7539124    .9614133
   formateur |    .130639   .0448604     2.91   0.020     .0271908    .2340873
       _cons |    .004002   .0089903     0.45   0.668    -.0167298    .0247337
------------------------------------------------------------------------------

. log close;
      name:  <unnamed>
       log:  C:\Users\sgolder\Dropbox\Portfolio Allocation\replication\africancabinets_multi_region.log
  log type:  text
 closed on:  30 Mar 2017, 13:37:13
------------------------------------------------------------------------------------------------------------------
